Modelling of changes in electricity end-use and their impacts on electricity distribution
Tuunanen, Jussi (2015-11-27)
Väitöskirja
Tuunanen, Jussi
27.11.2015
Lappeenranta University of Technology
Acta Universitatis Lappeenrantaensis
Julkaisun pysyvä osoite on
https://urn.fi/URN:ISBN:978-952-265-885-2
https://urn.fi/URN:ISBN:978-952-265-885-2
Tiivistelmä
The electricity distribution sector will face significant changes in the future. Increasing
reliability demands will call for major network investments. At the same time, electricity
end-use is undergoing profound changes. The changes include future energy technologies
and other advances in the field. New technologies such as microgeneration and electric
vehicles will have different kinds of impacts on electricity distribution network loads. In
addition, smart metering provides more accurate electricity consumption data and
opportunities to develop sophisticated load modelling and forecasting approaches. Thus,
there are both demands and opportunities to develop a new type of long-term forecasting
methodology for electricity distribution.
The work concentrates on the technical and economic perspectives of electricity
distribution. The doctoral dissertation proposes a methodology to forecast electricity
consumption in the distribution networks. The forecasting process consists of a spatial
analysis, clustering, end-use modelling, scenarios and simulation methods, and the load
forecasts are based on the application of automatic meter reading (AMR) data. The
developed long-term forecasting process produces power-based load forecasts. By
applying these results, it is possible to forecast the impacts of changes on electrical energy
in the network, and further, on the distribution system operator’s revenue. These results
are applicable to distribution network and business planning.
This doctoral dissertation includes a case study, which tests the forecasting process in
practice. For the case study, the most prominent future energy technologies are chosen,
and their impacts on the electrical energy and power on the network are analysed. The
most relevant topics related to changes in the operating environment, namely energy
efficiency, microgeneration, electric vehicles, energy storages and demand response, are
discussed in more detail.
The study shows that changes in electricity end-use may have radical impacts both on
electrical energy and power in the distribution networks and on the distribution revenue.
These changes will probably pose challenges for distribution system operators. The study
suggests solutions for the distribution system operators on how they can prepare for the
changing conditions. It is concluded that a new type of load forecasting methodology is
needed, because the previous methods are no longer able to produce adequate forecasts.
reliability demands will call for major network investments. At the same time, electricity
end-use is undergoing profound changes. The changes include future energy technologies
and other advances in the field. New technologies such as microgeneration and electric
vehicles will have different kinds of impacts on electricity distribution network loads. In
addition, smart metering provides more accurate electricity consumption data and
opportunities to develop sophisticated load modelling and forecasting approaches. Thus,
there are both demands and opportunities to develop a new type of long-term forecasting
methodology for electricity distribution.
The work concentrates on the technical and economic perspectives of electricity
distribution. The doctoral dissertation proposes a methodology to forecast electricity
consumption in the distribution networks. The forecasting process consists of a spatial
analysis, clustering, end-use modelling, scenarios and simulation methods, and the load
forecasts are based on the application of automatic meter reading (AMR) data. The
developed long-term forecasting process produces power-based load forecasts. By
applying these results, it is possible to forecast the impacts of changes on electrical energy
in the network, and further, on the distribution system operator’s revenue. These results
are applicable to distribution network and business planning.
This doctoral dissertation includes a case study, which tests the forecasting process in
practice. For the case study, the most prominent future energy technologies are chosen,
and their impacts on the electrical energy and power on the network are analysed. The
most relevant topics related to changes in the operating environment, namely energy
efficiency, microgeneration, electric vehicles, energy storages and demand response, are
discussed in more detail.
The study shows that changes in electricity end-use may have radical impacts both on
electrical energy and power in the distribution networks and on the distribution revenue.
These changes will probably pose challenges for distribution system operators. The study
suggests solutions for the distribution system operators on how they can prepare for the
changing conditions. It is concluded that a new type of load forecasting methodology is
needed, because the previous methods are no longer able to produce adequate forecasts.
Kokoelmat
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